Subtracting pandas Dataframe values from today's date

Question

I have a dataframe that looks like this:

Name  A    B    C
D1    1    3    3
D2    2    4    4
D3    2    1    1

How can I create a new dataframe of the same size where every value is today's date minus the value of my first dataframe?

for example, if today is 2018-04-27, my new dataframe would look like this:

Name  A             B             C  
D1    2018-04-26    2018-04-24    2018-04-24
D2    2018-04-25    2018-04-23    2018-04-23
D3    2018-04-25    2018-04-26    2018-04-26

I'm thinking the solution will include something like

df2.iloc[1,1] = datetime.today() - timedelta(days=df1[1,1])

but I'm running into all kinds of type errors and problems looping through the original df

Answer 1

import datetime as dt
from datetime import timedelta
import pandas as pd

df = pd.DataFrame({'Name':['D1','D2','D3'],'A':[1,2,2],'B':[3,4,1],'C':[3,4,1]})
df.set_index('Name', inplace=True)
df2 = df.applymap(lambda x: dt.date.today() - timedelta(days = x))

df2 
                   A           B           C
    Name
    D1    2018-04-26  2018-04-24  2018-04-24
    D2    2018-04-25  2018-04-23  2018-04-23
    D3    2018-04-25  2018-04-26  2018-04-26

Applymap is what you're looking to use

Edit: adding imports so that you avoid issues with datetime imports as seen here